Monday, December 26, 2005

FIP Analysis: Bonderman Better than his ERA

In an earlier post, I discussed team run prevention using FIP ERA to measure pitching performance and DER to measure fielding performance. In this post, I will evaluate the performance of individual starting pitchers using FIP ERA. There were 65 American League pitchers with 17 starts (approximately a half season) or more in 2005. The first table below lists Detroit Tiger starting pitchers in 2005 plus Kenny Rogers. The second table lists all 65 qualifiers in the league.



In both tables, ERA represents the pitcher’s actual ERA. FIP represents FIP ERA, the pitcher’s ERA based on fielding independent statistics (K,BB,HBP,HR) only. DER is the Defensive Efficiency Ratio of the team when the given pitcher was on the mound. A higher DER indicates that he received more fielding support. FIP-ERA is the difference between the pitcher’s FIP ERA and actual ERA. It tells how much the actual ERA was helped or hurt by non FIP factors. A negative number indicates that the pitcher probably pitched better than his actual ERA. A positive number says that he probably pitched worse than his actual ERA.



The tables show that Jeremy Bonderman had a FIP-ERA of -0.63 indicating that his relatively high actual ERA may have been due, in large part, to factors beyond his control. His DER (.690) was lower than any starting pitcher on the team which means that he received less fielding support than his pitching mates. While Bonderman’s actual ERA (4.57) was 41st in the league, his FIP ERA (3.94) was 16th. Since FIP ERA is a better predictor of future performance than actual ERA, this may bode well for next year.


On the other hand, Kenny Rogers had a much higher FIP ERA (4.11) than actual ERA (3.46). Rogers’s high DER (.714) says that he received a lot of fielding support. While his actual ERA was more than a run lower than Bonderman’s actual ERA, his FIP ERA was actually a little higher. It’s important to note that this analysis does not take ballpark into consideration. Obviously, Bonderman pitched in a more favorable environment but that’s a discussion for another time. The main point still stands. That is, Bonderman pitched better than his actual ERA and Rogers pitched worse than his actual ERA.


Jason Johnson (4.59 versus 4.39) and Mike Maroth (4.74 versus 4.69) both had FIP ERAs relatively close to their actual ERAs which says that there actual ERAs were probably pretty good indicators of their pitching performances. Nate Robertson had a FIP ERA (4.77) which was significantly higher than his actual ERA (4.48). This indicates that his pitching performance may have been overstated by his actual ERA. Robertson received the best fielding support (DER=.721) of any Tiger starting pitcher.


FIP Rnk

Name

Team

IP

ERA

FIP

DER

FIP- ERA

16

Bonderman

DET

189.0

4.57

3.94

.690

-0.63

24

Rogers

TEX

195.3

3.46

4.11

.714

0.65

31

Johnson

DET

210.0

4.54

4.39

.707

-0.16

46

Maroth

DET

209.0

4.74

4.69

.700

-0.05

47

Robertson

DET

196.7

4.48

4.77

.721

0.29

NA

Douglass

DET

87.3

5.56

4.94

.708

-0.62

NA

Ledezma

DET

49.7

7.07

6.04

.696

-1.02



FIP Rnk

Name

Team

IP

ERA

FIP

DER

FIP- ERA

1

Santana

MIN

231.7

2.87

2.84

.738

-0.04

2

Harden

OAK

128.0

2.53

2.94

.748

0.41

3

Halladay

TOR

141.7

2.41

3.08

.738

0.66

4

Lackey

LAA

209.0

3.44

3.14

.674

-0.30

5

Buehrle

CHA

236.7

3.12

3.46

.710

0.34

6

Bedard

BAL

141.7

4.00

3.53

.685

-0.47

7

Sabathia

CLE

196.7

4.03

3.73

.711

-0.29

8

Millwood

CLE

192.0

2.86

3.77

.719

0.91

9

Colon

LAA

222.7

3.48

3.79

.721

0.31

10

Kazmir

TB

186.0

3.77

3.80

.693

0.03

11

Johnson

NYA

225.7

3.79

3.82

.717

0.03

12

Lee

CLE

202.0

3.79

3.84

.723

0.05

13

Young

TEX

164.7

4.26

3.85

.709

-0.42

14

Wells

BOS

184.0

4.45

3.87

.680

-0.58

15

Haren

OAK

217.0

3.73

3.93

.713

0.20

16

Bonderman

DET

189.0

4.57

3.94

.690

-0.63

17

Byrd

LAA

204.3

3.74

3.98

.716

0.23

18

Towers

TOR

208.7

3.71

3.99

.698

0.28

19

Westbrook

CLE

210.7

4.49

4.00

.713

-0.48

20

Mussina

NYA

179.7

4.41

4.05

.678

-0.36

21

Cabrera

BAL

161.3

4.52

4.07

.709

-0.45

22

Clement

BOS

191.0

4.57

4.08

.701

-0.49

23

Garcia

CHA

228.0

3.87

4.09

.719

0.23

24

Rogers

TEX

195.3

3.46

4.11

.714

0.65

25

Park

TEX

109.7

5.66

4.19

.655

-1.47

26

Silva

MIN

188.3

3.44

4.23

.708

0.78

27

Wang

NYA

116.3

4.02

4.24

.735

0.22

28

Contreras

CHA

204.7

3.61

4.25

.742

0.64

29

Garland

CHA

221.0

3.50

4.28

.737

0.78

30

Chacin

TOR

203.0

3.72

4.30

.704

0.58

31

Johnson

DET

210.0

4.54

4.39

.707

-0.16

32

Washburn

LAA

177.3

3.20

4.39

.710

1.20

33

Zito

OAK

228.3

3.86

4.39

.757

0.52

34

Moyer

SEA

200.0

4.27

4.44

.704

0.16

35

Blanton

OAK

201.3

3.53

4.47

.752

0.94

36

Santana

LAA

133.7

4.65

4.47

.704

-0.18

37

Arroyo

BOS

205.3

4.51

4.48

.722

-0.04

38

Radke

MIN

200.7

4.04

4.48

.722

0.45

39

Pineiro

SEA

189.0

5.62

4.50

.681

-1.12

40

Saarloos

OAK

159.7

4.17

4.52

.712

0.34

41

Greinke

KC

183.0

5.80

4.53

.665

-1.27

42

Lohse

MIN

178.7

4.18

4.59

.689

0.41

43

Fossum

TB

162.7

4.92

4.61

.701

-0.32

44

Hendrickson

TB

178.3

5.90

4.67

.679

-1.23

45

Lopez

BAL

209.3

4.90

4.68

.709

-0.22

46

Maroth

DET

209.0

4.74

4.69

.700

-0.05

47

Robertson

DET

196.7

4.48

4.77

.721

0.29

48

Bush

TOR

136.3

4.49

4.79

.721

0.30

49

Ponson

BAL

130.3

6.21

4.79

.650

-1.43

50

Wakefield

BOS

225.3

4.15

4.79

.742

0.64

51

Hernandez

KC

159.7

5.52

4.87

.706

-0.65

52

Hernandez

CHA

128.3

5.12

4.92

.700

-0.20

53

Pavano

NYA

100.0

4.77

4.93

.673

0.16

54

Carrasco

KC

114.7

4.79

4.95

.701

0.16

55

Chen

BAL

197.3

3.83

4.98

.741

1.15

56

Mays

MIN

156.0

5.65

5.07

.681

-0.58

57

Franklin

SEA

190.7

5.10

5.08

.714

-0.02

58

Meche

SEA

143.3

5.09

5.09

.708

0.00

59

Elarton

CLE

181.7

4.61

5.11

.732

0.50

60

Waechter

TB

157.0

5.62

5.14

.697

-0.48

61

Lilly

TOR

126.3

5.56

5.36

.710

-0.20

62

Sele

SEA

116.0

5.66

5.36

.682

-0.31

63

Nomo

TB

100.7

7.24

5.54

.676

-1.71

64

McClung

TB

109.3

6.59

5.65

.731

-0.93

65

Lima

KC

168.7

6.99

5.75

.686

-1.24


2 comments:

  1. I like the fact that this effect is finally quantified. A lot of times you hear about a guy's defense and park having an effect on a pitcher's, but rarely is it quantified to the point where you can tell how much of an effect. I'm interested in what else you can do with this.

    ReplyDelete
  2. Edman, I'm reading eveything I can on defensive analysis. There is new stuff coming out all the time and the info is finally starting to become useful. I'll be posting about defense fairly regularly.

    ReplyDelete

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